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Courses

Envirotech - do-it-yourself sensors for environmental research

Image by Félix Girault

12 weekly classes (3 points)

About the Course

The objective of this course is to explore the integration of do-it-yourself (DIY) hardware, mainly open-source, low-cost microcontrollers and sensors, in environmental research. In this course, you will explore how the integrated use of this hardware type with concepts such as the Internet of Things (IoT) can be utilized to collect environmental data, automate processes, and improve environmental research. Throughout the course, you will gain practical knowledge on designing, developing, and implementing DIY-based solutions for different applications in environmental research, focusing on air, soil, water, and agricultural monitoring. For example, you will learn to use sensors to collect real-time temperature and CO  data from soils to calculate CO   emissions at the soil-atmosphere interface. This course is constructed for students interested in gaining hands-on experience in designing, coding, and implementing DIY-based sensor systems. By the end of this course, you will have a solid understanding of how to apply microcontrollers and sensors in environmental research, which will equip you with valuable skills for future research or professional opportunities. Although electronics and basic coding are the focus of this course, no previous engineering knowledge is needed – just motivation!

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We also offer a concentrated 4-day workshop focusing on the same subjects.

Prefer we come to your institute? Feel free to reach out 

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Field methods in hydrology

12 weekly classes (3 points)

About the Course

The main objective of this class is to expose the students to different methods of data acquisition and interpretation in different sections of hydrology: hydrometeorology, surface water, unsaturated and saturated zone and hydrology.  The student will practice the theoretical and technical aspects of common field methods through both class discussion and practical field application

ai_field hydrology course

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